Fetching the paper…
Reading the bibliography…
Adapters, a plug-in neural network module with some tunable parameters, have emerged as a parameter-efficient transfer learning technique for adapting pre-trained models to downstream tasks, especially for natural language processing (NLP) and computer vision (CV) fields.
Language models are few-shot learners
Tom Brown et al · 1901
Earlier work this paper cites.
Towards Unified Conversational Recommender Systems via Knowledge-Enhanced Prompt Learning. In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining . 1929–1937
Xiaolei Wang, Kun Zhou, Ji-Rong Wen, and Wayne Xin Zhao. 2022b · 1937
Earlier work this paper cites.
Modeling task relationships in multi-task learning with multi-gate mixture-of-experts. In Proceedings of the 24th ACM SIGKDD international conference on knowledge discovery & data mining . 1930–1939
Jiaqi Ma, Zhe Zhao, Xinyang Yi, Jilin Chen, Lichan Hong, and Ed H Chi. 2018 · 1939
Earlier work this paper cites.
Parameter-Efficient Transfer from Sequential Behaviors for User Modeling and Recommendation
Fajie Yuan, Xiangnan He, Alexandros Karatzoglou, and Liguang Zhang. 2020 · 2001
Earlier work this paper cites.
Transfer learning for collaborative filtering via a rating-matrix generative model. In Proceedings of the 26th annual international conference on machine learning . 617–624
Bin Li, Qiang Yang, and Xiangyang Xue. 2009 · 2009
Earlier work this paper cites.
Transfer learning in collaborative filtering for sparsity reduction. In Proceedings of the AAAI conference on artificial intelligence , Vol. 24. 230–235
Weike Pan, Evan Xiang, Nathan Liu, and Qiang Yang. 2010 · 2010
Earlier work this paper cites.
Transfer learning to predict missing ratings via heterogeneous user feedbacks. In Twenty-Second International Joint Conference on Artificial Intelligence
Weike Pan, Nathan N Liu, Evan W Xiang, and Qiang Yang. 2011 · 2011
Earlier work this paper cites.
Image-based recommendations on styles and substitutes. In Proceedings of the 38th international ACM SIGIR conference on research and development in information retrieval . 43–52
Julian McAuley, Christopher Targett, Qinfeng Shi, and Anton Van Den Hengel. 2015 · 2015
Earlier work this paper cites.
Ups and downs: Modeling the visual evolution of fashion trends with one-class collaborative filtering. In proceedings of the 25th international conference on world wide web . 507–517
Ruining He and Julian McAuley. 2016 · 2016
Earlier work this paper cites.
The adressa dataset for news recommendation. In Proceedings of the international conference on web intelligence . 1042–1048
Jon Atle Gulla, Lemei Zhang, Peng Liu, Özlem Özgöbek, and Xiaomeng Su. 2017 · 2017
Earlier work this paper cites.
Neural collaborative filtering. In Proceedings of the 26th international conference on world wide web . 173–182
Xiangnan He, Lizi Liao, Hanwang Zhang, Liqiang Nie, Xia Hu, and Tat-Seng Chua. 2017 · 2017
Earlier work this paper cites.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Earlier work this paper cites.
Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018 · 2018
Earlier work this paper cites.
Self-attentive sequential recommendation. In 2018 IEEE international conference on data mining (ICDM) . IEEE, 197–206
Wang-Cheng Kang and Julian McAuley. 2018 · 2018
Earlier work this paper cites.
Representation learning with contrastive predictive coding
Aaron van den Oord, Yazhe Li, and Oriol Vinyals. 2018 · 2018
Earlier work this paper cites.
Parameter-efficient transfer learning for NLP. In International Conference on Machine Learning . PMLR, 2790–2799
Neil Houlsby, Andrei Giurgiu, Stanislaw Jastrzebski, Bruna Morrone, Quentin De Laroussilhe, Andrea Gesmundo, Mona Attariyan, and Sylvain Gelly. 2019 · 2019
Earlier work this paper cites.
Roberta: A robustly optimized bert pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 2019
Earlier work this paper cites.
BERT4Rec: Sequential recommendation with bidirectional encoder representations from transformer. In Proceedings of the 28th ACM international conference on information and knowledge management . 1441–1450
Fei Sun, Jun Liu, Jian Wu, Changhua Pei, Xiao Lin, Wenwu Ou, and Peng Jiang. 2019 · 2019
Earlier work this paper cites.
An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, et al · 2020
Earlier work this paper cites.
On Sampled Metrics for Item Recommendation. In KDD
Walid Krichene and Steffen Rendle. 2020 · 2020
Earlier work this paper cites.
Adapterhub: A framework for adapting transformers
Jonas Pfeiffer, Andreas Rücklé, Clifton Poth, Aishwarya Kamath, Ivan Vulić, Sebastian Ruder, Kyunghyun Cho, and Iryna Gurevych. 2020a · 2020
Earlier work this paper cites.
Mad-x: An adapter-based framework for multi-task cross-lingual transfer
Jonas Pfeiffer, Ivan Vulić, Iryna Gurevych, and Sebastian Ruder. 2020b · 2020
Earlier work this paper cites.
Multi-modal knowledge graphs for recommender systems. In Proceedings of the 29th ACM international conference on information & knowledge management . 1405–1414
Rui Sun, Xuezhi Cao, Yan Zhao, Junchen Wan, Kun Zhou, Fuzheng Zhang, Zhongyuan Wang, and Kai Zheng. 2020 · 2020
Earlier work this paper cites.
K-adapter: Infusing knowledge into pre-trained models with adapters
Ruize Wang, Duyu Tang, Nan Duan, Zhongyu Wei, Xuanjing Huang, Guihong Cao, Daxin Jiang, Ming Zhou, et al · 2020
Earlier work this paper cites.
Mind: A large-scale dataset for news recommendation. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics . 3597–3606
Fangzhao Wu, Ying Qiao, Jiun-Hung Chen, Chuhan Wu, Tao Qi, Jianxun Lian, Danyang Liu, Xing Xie, Jianfeng Gao, Winnie Wu, et al · 2020
Earlier work this paper cites.
On the opportunities and risks of foundation models
Rishi Bommasani, Drew A Hudson, Ehsan Adeli, Russ Altman, Simran Arora, Sydney von Arx, Michael S Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, et al · 2021
Cited alongside, same era.
Hao Ding, Yifei Ma, Anoop Deoras, Yuyang Wang, and Hao Wang. 2021 · 2021
Cited alongside, same era.
Robust transfer learning with pretrained language models through adapters
Wenjuan Han, Bo Pang, and Yingnian Wu. 2021 · 2021
Cited alongside, same era.
Lora: Low-rank adaptation of large language models
Edward J Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen. 2021 · 2021
Cited alongside, same era.
Compacter: Efficient low-rank hypercomplex adapter layers
VL-Adapter: Parameter-Efficient Transfer Learning for Vision-and-Language Tasks. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) . 5227–5237
Yi-Lin Sung, Jaemin Cho, and Mohit Bansal. 2022 · 2022
Later among the works it cites.
Transrec: Learning transferable recommendation from mixture-of-modality feedback
Jie Wang, Fajie Yuan, Mingyue Cheng, Joemon M Jose, Chenyun Yu, Beibei Kong, Xiangnan He, Zhijin Wang, Bo Hu, and Zang Li. 2022a · 2022
Later among the works it cites.
End-to-end Learnable Diversity-aware News Recommendation
Chuhan Wu, Fangzhao Wu, Tao Qi, and Yongfeng Huang. 2022a · 2022
Later among the works it cites.
Personalized Prompts for Sequential Recommendation
Yiqing Wu, Ruobing Xie, Yongchun Zhu, Fuzhen Zhuang, Xu Zhang, Leyu Lin, and Qing He. 2022c · 2022
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Rabeeh Karimi Mahabadi, James Henderson, and Sebastian Ruder. 2021 · 2021
Cited alongside, same era.
The power of scale for parameter-efficient prompt tuning
Brian Lester, Rami Al-Rfou, and Noah Constant. 2021 · 2021
Cited alongside, same era.
Swin Transformer: Hierarchical Vision Transformer Using Shifted Windows. In Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) . 10012–10022
Ze Liu, Yutong Lin, Yue Cao, Han Hu, Yixuan Wei, Zheng Zhang, Stephen Lin, and Baining Guo. 2021 · 2021
Cited alongside, same era.
Learning transferable visual models from natural language supervision. In International conference on machine learning . PMLR, 8748–8763
Alec Radford, Jong Wook Kim, et al · 2021
Cited alongside, same era.
One model to serve all: Star topology adaptive recommender for multi-domain ctr prediction. In Proceedings of the 30th ACM International Conference on Information & Knowledge Management . 4104–4113
Xiang-Rong Sheng, Liqin Zhao, Guorui Zhou, Xinyao Ding, Binding Dai, Qiang Luo, Siran Yang, Jingshan Lv, Chi Zhang, Hongbo Deng, et al · 2021
Cited alongside, same era.
One4all user representation for recommender systems in e-commerce
Kyuyong Shin, Hanock Kwak, Kyung-Min Kim, Minkyu Kim, Young-Jin Park, Jisu Jeong, and Seungjae Jung. 2021b · 2021
Cited alongside, same era.
Scaling Law for Recommendation Models: Towards General-purpose User Representations
Kyuyong Shin, Hanock Kwak, Kyung-Min Kim, Su Young Kim, and Max Nihlen Ramstrom. 2021a · 2021
Cited alongside, same era.
Mm-rec: multimodal news recommendation
Chuhan Wu, Fangzhao Wu, Tao Qi, and Yongfeng Huang. 2021b · 2021
Cited alongside, same era.
Training large-scale news recommenders with pretrained language models in the loop. In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining . 4215–4225
Shitao Xiao, Zheng Liu, Yingxia Shao, Tao Di, Bhuvan Middha, Fangzhao Wu, and Xing Xie. 2022 · 2022
Later among the works it cites.
Rethinking Reinforcement Learning for Recommendation: A Prompt Perspective. In Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval . 1347–1357
Xin Xin, Tiago Pimentel, Alexandros Karatzoglou, Pengjie Ren, Konstantina Christakopoulou, and Zhaochun Ren. 2022 · 2022
Later among the works it cites.
Keqin Bao, Jizhi Zhang, Yang Zhang, Wenjie Wang, Fuli Feng, and Xiangnan He. 2023 · 2023
Closest in time.
An Image Dataset for Benchmarking Recommender Systems with Raw Pixels
Yu Cheng, Yunzhu Pan, Jiaqi Zhang, Yongxin Ni, Aixin Sun, and Fajie Yuan. 2023 · 2023
Closest in time.
Llama-adapter v2: Parameter-efficient visual instruction model
Peng Gao, Jiaming Han, Renrui Zhang, Ziyi Lin, Shijie Geng, Aojun Zhou, Wei Zhang, Pan Lu, Conghui He, Xiangyu Yue, et al · 2023
Closest in time.
ALGRNet: Multi-Relational Adaptive Facial Action Unit Modelling for Face Representation and Relevant Recognitions
Xuri Ge, Joemon M Jose, Pengcheng Wang, Arunachalam Iyer, Xiao Liu, and Hu Han. 2023 · 2023
Closest in time.
VIP5: Towards Multimodal Foundation Models for Recommendation
Shijie Geng, Juntao Tan, Shuchang Liu, Zuohui Fu, and Yongfeng Zhang. 2023 · 2023
Closest in time.
Prompt Tuning Large Language Models on Personalized Aspect Extraction for Recommendations
Pan Li, Yuyan Wang, Ed H Chi, and Minmin Chen. 2023b · 2023
Closest in time.
Ruyu Li, Wenhao Deng, Yu Cheng, Zheng Yuan, Jiaqi Zhang, and Fajie Yuan. 2023a · 2023
Closest in time.
ID Embedding as Subtle Features of Content and Structure for Multimodal Recommendation
Yuting Liu, Enneng Yang, Yizhou Dang, Guibing Guo, Qiang Liu, Yuliang Liang, Linying Jiang, and Xingwei Wang. 2023 · 2023
Closest in time.
A Content-Driven Micro-Video Recommendation Dataset at Scale
Yongxin Ni, Yu Cheng, Xiangyan Liu, Junchen Fu, Youhua Li, Xiangnan He, Yongfeng Zhang, and Fajie Yuan. 2023 · 2023
Closest in time.
Thoroughly Modeling Multi-domain Pre-trained Recommendation as Language
Zekai Qu, Ruobing Xie, Chaojun Xiao, Yuan Yao, Zhiyuan Liu, Fengzong Lian, Zhanhui Kang, and Jie Zhou. 2023 · 2023
Closest in time.
Recommender Systems with Generative Retrieval
Shashank Rajput, Nikhil Mehta, Anima Singh, Raghunandan H Keshavan, Trung Vu, Lukasz Heldt, Lichan Hong, Yi Tay, Vinh Q Tran, Jonah Samost, et al · 2023
Closest in time.
MISSRec: Pre-training and Transferring Multi-modal Interest-aware Sequence Representation for Recommendation. In Proceedings of the 31st ACM International Conference on Multimedia . 6548–6557
Jinpeng Wang, Ziyun Zeng, Yunxiao Wang, Yuting Wang, Xingyu Lu, Tianxiang Li, Jun Yuan, Rui Zhang, Hai-Tao Zheng, and Shu-Tao Xia. 2023 · 2023
Closest in time.
Multi-Modal Self-Supervised Learning for Recommendation. In Proceedings of the ACM Web Conference 2023 . 790–800
Wei Wei, Chao Huang, Lianghao Xia, and Chuxu Zhang. 2023 · 2023
Closest in time.
Collaborative Word-based Pre-trained Item Representation for Transferable Recommendation
Shenghao Yang, Chenyang Wang, Yankai Liu, Kangping Xu, Weizhi Ma, Yiqun Liu, Min Zhang, Haitao Zeng, Junlan Feng, and Chao Deng. 2023 · 2023
Closest in time.
Where to go next for recommender systems? id-vs. modality-based recommender models revisited
Zheng Yuan, Fajie Yuan, Yu Song, Youhua Li, Junchen Fu, Fei Yang, Yunzhu Pan, and Yongxin Ni. 2023 · 2023
Closest in time.
NineRec: A Benchmark Dataset Suite for Evaluating Transferable Recommendation
Jiaqi Zhang, Yu Cheng, Yongxin Ni, Yunzhu Pan, Zheng Yuan, Junchen Fu, Youhua Li, Jie Wang, and Fajie Yuan. 2023a · 2023
Closest in time.
Llama-adapter: Efficient fine-tuning of language models with zero-init attention
Renrui Zhang, Jiaming Han, Aojun Zhou, Xiangfei Hu, Shilin Yan, Pan Lu, Hongsheng Li, Peng Gao, and Yu Qiao. 2023b · 2023
Closest in time.
Prompt learning for news recommendation
Zizhuo Zhang and Bang Wang. 2023 · 2023
Closest in time.